updated T() from I(); incorporated CRAN suggestion

DESCRIPTION

@@ -1,8 +1,8 @@
 Package: baker
 Type: Package
-Title: Nested Partially Latent Class Models
+Title: "Nested Partially Latent Class Models"
 Version: 1.0.2
-Date: 2023-12-18
+Date: 2023-12-20
 Authors@R: c(
      person("Zhenke", "Wu", email="zhenkewu@gmail.com",role=c("cre","aut","cph"),
      comment = c(ORCID = "0000-0001-7582-669X")),
@@ -15,13 +15,13 @@ Authors@R: c(
      )
 Description: Provides functions to specify, fit and visualize
     nested partially-latent class models (
-    'Wu, Deloria-Knoll, Hammitt, and Zeger, 2016, JRSS-C' <doi:10.1111/rssc.12101>; 
-    'Wu, Deloria-Knoll, and Zeger, 2017, Biostatistics' <doi:10.1093/biostatistics/kxw037>;
-    'Wu and Chen, 2021, Statistics in Medicine' <doi:10.1002/sim.8804>) for 
+    Wu, Deloria-Knoll, Hammitt, and Zeger (2016) <doi:10.1111/rssc.12101>; 
+    Wu, Deloria-Knoll, and Zeger (2017) <doi:10.1093/biostatistics/kxw037>;
+    Wu and Chen (2021) <doi:10.1002/sim.8804>) for 
     inference of population disease etiology and individual diagnosis. In the motivating
     Pneumonia Etiology Research for Child Health (PERCH) study, because both quantities
     of interest sum to one hundred percent, the PERCH scientists frequently refer to
-    them as 'population etiology pie' and 'individual etiology pie', hence the name of the package.
+    them as population etiology pie and individual etiology pie, hence the name of the package.
 Depends:
     R(>= 4.3.0)
 Imports:

R/eda.R

@@ -132,7 +132,8 @@ plot_logORmat = function(data_nplcm,
     cex_main= min(2,20/n)
     cex_se  = min(1.5,15/n)
 
-    graphics::par(mar = c(0, 1, 5, 0), bg = "white",xpd=TRUE)
+    op <- graphics::par(mar = c(0, 1, 5, 0), bg = "white",xpd=TRUE)
+    on.exit(par(op))
     graphics::plot(c(0, n + 0.8), c(0, n + 0.8), axes = axes, xlab = "",
          ylab = "", asp = 1, type = "n")
     ##add grid

R/nplcm.R

@@ -1015,7 +1015,7 @@ nplcm_fit_NoReg<-
     curr_model_txt_file <- file.path(mcmc_options$result.folder,model_bugfile_name)
     bad_model_txt <- readLines(curr_model_txt_file)
     good_model_txt <- gsub( "cut\\(", "(", bad_model_txt,fixed = FALSE)
-    good_model_txt <- gsub( "I\\(0\\.000001,0\\.999999\\)", " ", good_model_txt,fixed = FALSE)
+    # good_model_txt <- gsub( "I\\(0\\.000001,0\\.999999\\)", " ", good_model_txt,fixed = FALSE)
     writeLines(good_model_txt, curr_model_txt_file)
 
     if(is.null(mcmc_options$jags.dir)){mcmc_options$jags.dir=""}
@@ -1772,7 +1772,7 @@ nplcm_fit_Reg_discrete_predictor_NoNest <-
     curr_model_txt_file <- file.path(mcmc_options$result.folder,model_bugfile_name)
     bad_model_txt <- readLines(curr_model_txt_file)
     good_model_txt <- gsub( "cut\\(", "(", bad_model_txt,fixed = FALSE)
-    good_model_txt <- gsub( "I\\(0\\.000001,0\\.999999\\)", " ", good_model_txt,fixed = FALSE)
+    # good_model_txt <- gsub( "I\\(0\\.000001,0\\.999999\\)", " ", good_model_txt,fixed = FALSE)
     writeLines(good_model_txt, curr_model_txt_file)
 
     if(is.null(mcmc_options$jags.dir)){mcmc_options$jags.dir=""}
@@ -2461,7 +2461,7 @@ nplcm_fit_Reg_NoNest <-
       curr_model_txt_file <- file.path(mcmc_options$result.folder,model_bugfile_name)
       bad_model_txt <- readLines(curr_model_txt_file)
       good_model_txt <- gsub( "cut\\(", "(", bad_model_txt,fixed = FALSE)
-      good_model_txt <- gsub( "I\\(0\\.000001,0\\.999999\\)", " ", good_model_txt,fixed = FALSE)
+      # good_model_txt <- gsub( "I\\(0\\.000001,0\\.999999\\)", " ", good_model_txt,fixed = FALSE)
       writeLines(good_model_txt, curr_model_txt_file)
 
       if(is.null(mcmc_options$jags.dir)){mcmc_options$jags.dir=""}
@@ -3223,7 +3223,7 @@ nplcm_fit_Reg_Nest <- function(data_nplcm,model_options,mcmc_options){
   curr_model_txt_file <- file.path(mcmc_options$result.folder,model_bugfile_name)
   bad_model_txt <- readLines(curr_model_txt_file)
   good_model_txt <- gsub( "cut\\(", "(", bad_model_txt,fixed = FALSE)
-  good_model_txt <- gsub( "I\\(0\\.000001,0\\.999999\\)", " ", good_model_txt,fixed = FALSE)
+  # good_model_txt <- gsub( "I\\(0\\.000001,0\\.999999\\)", " ", good_model_txt,fixed = FALSE)
   writeLines(good_model_txt, curr_model_txt_file)
 
   if(is.null(mcmc_options$jags.dir)){mcmc_options$jags.dir=""}

R/plot-etiology-regression.R

@@ -288,13 +288,15 @@ plot_etiology_regression <- function(DIR_NPLCM,stratum_bool,slice=1,plot_basis=F
   # plot results:
   #################
   if (do_plot){  
-    par(mfcol=c(2,Jcause),oma=c(3,0,3,0))
+    op <- par(mfcol=c(2,Jcause),oma=c(3,0,3,0))
+    on.exit(par(op))
     for (j in 1:Jcause){ # <--- the marginal dimension of measurements.
       # need to fix this for NoA! <------------------------ FIX!
       #
       # Figure 1 for case and control positive rates:
       #
-      par(mar=c(2,5,0,1))
+      op1 <- par(mar=c(2,5,0,1))
+      on.exit(par(op1))
       #<------------------------ FIX!
       if (model_options$likelihood$cause_list[j] == "other"){
         plot(0,0.5,type="l",ylim=c(0,1),pch="n",
@@ -376,7 +378,8 @@ plot_etiology_regression <- function(DIR_NPLCM,stratum_bool,slice=1,plot_basis=F
       #
       # Figure 2 for Etiology Regression:
       #
-      par(mar=c(2,5,0,1))
+      op2 <- par(mar=c(2,5,0,1))
+      on.exit(par(op2))
       plot(curr_date_Eti,Eti_mean[j,],type="l",ylim=c(0,1),xlab="standardized date",
            ylab=c("","etiologic fraction")[(j==1)+1],bty="n",xaxt="n",yaxt="n",las=2)
       ## ONLY FOR SIMULATIONS <---------------------- FIX!
@@ -614,6 +617,7 @@ plot_subwt_regression <- function(DIR_NPLCM,stratum_bool,case=0,slice=1,truth=NU
 #' @param show_levels a vector of integers less than or equal to the total number of 
 #' levels of strata; default to `0` for overall.
 #' @param is_plot default to TRUE, plotting the figures; if `FALSE` only returning summaries
+#' @param VERBOSE default to `TRUE`, print actual meanings of the levels
 #' @import graphics ggplot2
 #' @importFrom ggpubr ggarrange
 #' @importFrom stats aggregate
@@ -623,7 +627,7 @@ plot_subwt_regression <- function(DIR_NPLCM,stratum_bool,case=0,slice=1,truth=NU
 #' @return plotting function
 plot_etiology_strat <- function(DIR_NPLCM,strata_weights = "empirical",
                                 truth=NULL,
-                                RES_NPLCM=NULL,show_levels=0,is_plot=TRUE){
+                                RES_NPLCM=NULL,show_levels=0,is_plot=TRUE,VERBOSE=TRUE){
   # ### test
   # DIR_NPLCM = result_folder_discrete
   # strata_weights = "empirical"
@@ -868,8 +872,12 @@ plot_etiology_strat <- function(DIR_NPLCM,strata_weights = "empirical",
       }
     }
 
-    print("==[baker] actual meanings of levels (by row):")
-    print(unique_Eti_level)
+    if(VERBOSE){
+      print("==[baker] actual meanings of levels (by row):")
+      print(unique_Eti_level)
+    }
+    # this following is plotting, because this is a plotting function to be fed
+    # into a genric plot function, so we keep it out of VERBOSE if else logic:
     print(ggpubr::ggarrange(plotlist=plot_list_show,nrow = length(plot_list_show)))
   }
 

R/plot-panels.R

@@ -266,6 +266,7 @@ get_plot_num <- function(e, height){
 plot_leftmost <- function(model_options,height){
 
   op <- graphics::par(mar=c(5.1,4,4.1,0))
+  on.exit(par(op))
   graphics::plot(rep(0,3*height),
                  c(sapply(1:height,get_plot_num,height)),
                  xlim=c(0,0.1),
@@ -675,6 +676,7 @@ plot_BrS_panel <- function(slice,data_nplcm,model_options,
   #
   #op <- graphics::par(mar=c(5.1,4.1,4.1,0))
   op <- graphics::par(mar=c(5.1,0,4.1,0))
+  on.exit(par(op))
 
   if (!is_length_all_one(pos_vec)){
     #stop("== Not implemented for combo latent status.==")
@@ -1277,6 +1279,7 @@ plot_SS_panel <- function(slice,data_nplcm,model_options,
   # plotting:
   #
   op <- graphics::par(mar=c(5.1,0,4.1,0))
+  on.exit(par(op))
 
   if (check_combo_SS){
     #stop("== Not implemented for combo latent status.==")

R/utils.R

@@ -403,7 +403,9 @@ visualize_case_control_matrix <- function(mat, dim_names = ncol(mat),
   cex_main = min(2,20 / n)
   cex_se  = min(1.5,15 / n)
 
-  graphics::par(mar = c(0, 0, 5, 0), bg = "white",xpd = TRUE)
+  op <- graphics::par(mar = c(0, 0, 5, 0), bg = "white",xpd = TRUE)
+  on.exit(par(op))
+
   graphics::plot(
     c(0, n + 0.8), c(0, n + 0.8), axes = axes, xlab = "",
     ylab = "", asp = 1, type = "n"

R/write-model.R

@@ -1272,7 +1272,7 @@ add_meas_BrS_param_Nest_Slice <- function(s,Mobs,cause_list) { #note: has separa
     ",r0_nm[s],"[",K_nm[s],"]<-1
     for(j in 2:",K_nm[s],") {",Lambda0_nm[s],"[j]<-",r0_nm[s],"[j]*(1-",r0_nm[s],"[j-1])*",Lambda0_nm[s],"[j-1]/",r0_nm[s],"[j-1]}
     for(k in 1:(",K_nm[s],"-1)){
-    ",r0_nm[s],"[k]~dbeta(1,",alphadp0_nm[s],")I(0.000001,0.999999)
+    ",r0_nm[s],"[k]~dbeta(1,",alphadp0_nm[s],")T(0.000001,0.999999)
     }
     
     for (k in 1:(",K_nm[s],"-1)){",Lambda_nm[s],"[k]<-max(0.000001,min(0.999999,",Lambda0_nm[s],"[k]))}
@@ -1283,7 +1283,7 @@ add_meas_BrS_param_Nest_Slice <- function(s,Mobs,cause_list) { #note: has separa
     ",r1_nm[s],"[",K_nm[s],"]<-1
     for(j in 2:",K_nm[s],") {",Eta0_nm[s],"[j]<-",r1_nm[s],"[j]*(1-",r1_nm[s],"[j-1])*",Eta0_nm[s],"[j-1]/",r1_nm[s],"[j-1]}
     for(k in 1:(",K_nm[s],"-1)){
-    ",r1_nm[s],"[k]~dbeta(1,",alphadp0_case_nm[s],")I(0.000001,0.999999)
+    ",r1_nm[s],"[k]~dbeta(1,",alphadp0_case_nm[s],")T(0.000001,0.999999)
     }
     
     for (k in 1:(",K_nm[s],"-1)){",Eta_nm[s],"[k]<-max(0.000001,min(0.999999,",Eta0_nm[s],"[k]))}

cran-comments.md

@@ -1,12 +1,34 @@
 ## Resubmission
 This is a resubmission. In this version I have:
 
-* updated to fix an issue in the example of `nplcm` (Package was archived on CRAN because of a tricky interfacing issue between JAGS 4.3.x and R 4.3.x was not corrected in time)
+* Fixed an issue related to JAGS being updated to 4.3.x 
+(Package was archived on CRAN because of a tricky interfacing issue between 
+JAGS 4.3.x and R 4.3.x was not corrected in time); I contacted the author of JAGS and he confirmed the issue
+was a bug but will not release a debugged version soon. So I went ahead to fix the issue 
+in my package; the changes primarily occurred in the `jags2_baker` function which interfaces with
+the JAGS. Also JAGS 4.3.x retired a function`cut` so I modified the functoins in `nplcm.R` to accommodate this change.
+  - And these fixes passes the suggested checks (see Test `Environments` below). 
+
+* winbuilder gave a note on new submission and possible misspelling - but because
+I was intructed to not put single quotes around these names (which would overcome this issue),
+I will leave as is.
+
+  - ```
+    New submission
+    
+    Package was archived on CRAN
+    
+    Possibly misspelled words in DESCRIPTION:
+      Deloria (18:9, 19:9)
+      Hammitt (18:24)
+      Zeger (18:37, 19:28)
+  ```
 
 ## Reverse dependencies; revdecp_check result `OK: 0` `BROKEN: 0`
 
-This is a precise fix to a previously a short and archived release taken down on 2022-06-08 (https://cran.r-project.org/web/packages/baker/index.html), so there are no reverse dependencies
-given the short life of the previous release.
+This is a precise fix to a previously a short and archived release taken down on 
+2022-06-08 (https://cran.r-project.org/web/packages/baker/index.html), 
+so there are no reverse dependencies given the short life of the previous release.
 
 
 ## Test environments